AI Engineer

Job Description & Requirements

Design, build, and deploy AI agents for operational workflows.

· Integrate agents with enterprise systems (ERP, HRIS, SharePoint, Dynamics 365, Salesforce) via APIs, Power Automate, or Graph connectors.

· Implement agent telemetry and observability pipelines using Microsoft Fabric or Power BI.

· Apply RAG (Retrieval-Augmented Generation), context injection, and prompt-chaining for knowledge-aware automation if needed.

· Maintain security, versioning, and audit trails for all agent deployments.

· Perform exploratory data analysis (EDA) on Finance, HR, or current datasets to identify automation opportunities and trends.

· Develop predictive ML models (e.g. anomaly detection, risk scoring).

· Deploy ML models into Power BI or agents through Fabric ML endpoints, or Python scripts.

· Collaborate with BI team to transform model output into decision-ready dashboards and alerts.

· Continuously measure ROI and performance through agent telemetry and statistical evaluation.

· Partner with the AI BA to translate business logic into model features and automation workflows.

· Work with BI teams to ensure data readiness, integrity, and lineage.

· Document models, pipelines, and prompts for auditability and reproducibility.

Qualifications

· Bachelor’s or Master’s degree in Computer Science, Data Science, or related field.

· 4–8 years’ experience in data engineering, machine learning, or automation.

· Strong proficiency in Python, SQL, and Power Platform (Power Automate, Copilot Studio, Power Apps).

· Hands-on experience with EDA, regression/classification models, clustering, anomaly detection, and time-series forecasting.

· Familiarity with Azure AI / Azure Machine Learning / Fabric ML environment.

· Understanding of RAG pipelines, prompt-engineering, and LLM integration a plus.

· Experience working with structured (ERP, Finance, HR) and semi-structured data (documents, logs).

· Strong communication skills — can explain technical solutions to non-technical stakeholders.

· Bonus: Exposure to Finance or Shared-Service operations preferred.